The present invention relates to a device and method for analyzing agricultural products. More particularly, the present invention relates to a device and method for real time, non-destructive analysis of the physical and chemical characteristics of one or more seeds.
Breeding for compositionally enhanced agricultural products can require the analysis of a large number of seed samples from plants to identify those plants with the desired compositional and agronomic properties for use or advancement to the next generation. Analysis of bulk seed batches for certain traits, such as high oil or high protein, on a single plant or ear, in conjunction with an appropriate breeding methodology such as recurrent selection, often allow for the selection of and introduction of such traits into a commercial population. Although the analysis of these seed batches can be performed by various techniques, typically methods that are rapid, low cost, and non-destructive are used.
During the past decade, near infrared (NIR) spectroscopy has become a standard method for screening seed samples whenever the sample of interest has been amenable to this technique. Samples studied include wheat, maize, soybean, canola, rice, alfalfa, oat, and others (see, for example, Massie and Norris, xe2x80x9cSpectral Reflectance and Transmittance Properties of Grain in the Visible and Near Infraredxe2x80x9d, Transactions of the ASAE, Winter Meeting of the American society of Agricultural Engineers, 1965, pp. 598-600, which is herein incorporated by reference in its entirety). NIR spectroscopy uses near infrared light, which is typically in the range of 770 to 2,500 nanometers, to access overtones and combinations of the fundamental vibrational frequencies of the organic functional groups of Oxe2x80x94H, Cxe2x80x94H, and Nxe2x80x94H. Devices for measuring such light are known in the art. (See, for example Hyvarinen et al., xe2x80x9cDirect Sight Imaging Spectrograph: A Unique Add-on Component Brings Spectral Imaging to Industrial Applicationsxe2x80x9d, SPIE Vol. 3,302, 1998, xe2x80x9cHandbook of Near-Infrared Analysisxe2x80x9d, Eds. Burns and Ciurczak, Marcel Dekker, Inc., 1992, both of which are herein incorporated by reference in their entirety).
Typically, the NIR spectra associated with a batch of seeds is determined (often, for example, a cuvette capable of holding 100 grams of seed is used). This determination can be combined with conventional chemical analysis of samples in order to provide additional data and to build a chemometric calibration model. Chemometric calibration models are often developed for traits that include, but are not limited to: oil, starch, water, fiber, protein, extractable starch, chlorophyll, glucosinolates, and fatty acid (see, for example, Archibald et al. xe2x80x9cDevelopment of Short-Wavelength Near-Infrared spectral Imaging for Grain Color Classification,xe2x80x9d SPIE Vol. 3,543, 1998, pp. 189-198, Delwiche, xe2x80x9cSingle Wheat Kernel Analysis by Near-Infrared Transmittance: Protein Content,xe2x80x9d Analytical Techniques and Instrumentation, Vol. 72, 1995, pp. 11-16, Dowell, xe2x80x9cAutomated Color Classification of single Wheat Kernels Using Visible and Near-Infrared Reflectance,xe2x80x9d Vol. 75(1), 1998, pp. 142-144, Orman and Schumann, xe2x80x9cComparison of Near-Infrared Spectroscopy Calibration Methods for the Prediction of Protein, Oil, and Starch in Maize Grain,xe2x80x9d Vol. 39, 1991, pp.883-886, Robutti, xe2x80x9cMaize Kernel Hardness Estimation in Breeding by Near-Infrared Transmission Analysis,xe2x80x9d Vol. 72(6), 1995, pp.632-636, U.S. Pat. No. 5,991,025, U.S. Pat. No. 5,751,421, Daun et al., xe2x80x9cComparison of Three whole Seed Near-Infrared Analyzers for Measuring Quality Components of Canola Seedxe2x80x9d, Vol. 71, no. 10, 1994, pp. 1,063-1,068, xe2x80x9cCorn: Chemistry and Technologyxe2x80x9d, Eds. Watson and Ramstad, American Association of Cereal Chemists, Inc., (1987), all of which are herein incorporated by reference in their entirety). The development of a chemometric model can then be used to predict the chemical characteristics of untested samples with NIR spectroscopy, without requiring additional conventional chemical analysis.
NIR analysis of bulk samples, either crushed or whole, has been reported (see, for example, Orman and Schumann, xe2x80x9cComparison of Near-Infrared Spectroscopy Calibration Methods for the Prediction of Protein, Oil, and Starch in Maize Grain,xe2x80x9d Vol. 39, 1991, pp.883-886, Robutti, xe2x80x9cMaize Kernel Hardness Estimation in Breeding by Near-Infrared Transmission Analysis,xe2x80x9d Vol. 72(6), 1995, pp.632-636, U.S. Pat. No. 5,991,025, U.S. Pat. No. 5,751,421, Daun et al., xe2x80x9cComparison of Three whole Seed Near-Infrared Analyzers for Measuring Quality Components of Canola Seedxe2x80x9d, Vol. 71, no. 10, 1994, pp.1,063-1,068, all of which are herein incorporated by reference in their entirety). Conventional commercial NIR spectrometers for bulk grain analysis have several disadvantages. Conventional spectrometers were designed for use in a laboratory environment, which is typically distant from the breeding fields, under controlled conditions of temperature, humidity and vibration. In addition, the spectrometers necessitate excessive sample handling. The samples must be harvested, sent to the breeding facility, threshed, bagged, labeled, and sent to the NIR lab for analysis. At the NIR lab the samples must be logged in, removed from the sample bags, poured into the sample cuvette, scanned with the NIR spectrometer, returned to the original sample bag, and sent back to the breeding facility. The resulting NIR data must be assembled into a final report, reviewed for any anomalies, and sent back to the breeder, who then locates and sorts the samples based upon the NIR analytical results. The excessive sample handling adds both time and cost to the analysis.
Current NIR based approaches are not only cumbersome and expensive, they are slow. Data processing time can be crucial because selection of appropriate seeds should be carried out prior to the planting time of the next generation. Delays in providing the breeder with the analytical results or the return of the samples can result in the loss of an entire breeding cycle.
Further, the speed of acquisition and analysis of the current technology cannot keep up with the speed at which the processing devices can operate. For example, single ear shellers can process up to 15 ears of corn per minute. Current NIR commercial spectrometers operate at a rate of about one sample every one to two minutes. The spectrometer rate of processing is typically the limiting step in the analytical process.
Conventional spectrometers gather information from a sub-set of the total sample. Commercial spectrometers collect light at a single point or several tens of points with small active areas, which results in only a small portion of the sample actually being interrogated by the technique. In bulk samples, for example, conventional techniques can lead to spot sampling of portions of only a few seeds out of the hundreds of seeds in the bulk sample. Further, since spot sampling of bulk samples analyzes arbitrary portions of the seed, different tissues of the seeds in the samples can be misrepresented by the analytical data. Since qualities like oil content are often present in different amounts in different tissues, these conventional techniques can fail to accurately assess the desired quality. These limitations apply to spectrometers with conventional optical configurations where a lens system collects light from the sample, as well as those that use fiber optic bundles to collect the light from the sample. In addition, since discrete, unrelated sampling points are used, spatial information associated with the sample is lost. Spatial information (which can be used, for instance, to determine morphology) consists of, for example, size, shape, mechanical damage, insect infestation, and fungal damage. Since conventional spectrometers do not collect spatial information at all, a correlation of spatial and spectral data is not possible.
Conventional spectrometers also fail to provide an efficient method for single seed analysis, which can greatly accelerate the rate of varietal development. Single seed analysis is necessary to differentiate and select seed present within a heterogeneous population of seeds. Heterogeneous populations of seed are often encountered in breeding populations. Single seed analysis can reduce the number of generations required for the production of a plant with the desired trait. Single seed selection also reduces the number of individual plants required. In corn, for example, the ability to identify the individual seeds with the desired trait at the single seed level rather than at the whole ear level can reduce the nursery requirement by 100 fold. This makes it possible to conduct a far greater number of breeding projects with the same resources.
NIR analysis of single seeds has also been reported (see Delwiche, xe2x80x9cSingle Wheat Kernel Analysis by Near-Infrared Transmittance: Protein Content,xe2x80x9d Analytical Techniques and Instrumentation, Vol. 72, 1995, pp. 11-16, Dowell, xe2x80x9cAutomated Color Classification of single Wheat Kernels Using Visible and Near-Infrared Reflectance,xe2x80x9d Vol. 75(1), 1998, pp. 142-144, Dowell et al., xe2x80x9cAutomated Single Wheat Kernel Quality Measurement Using Near-Infrared Reflectance,xe2x80x9d ASAE Annual International Meeting, 1997, paper number 973022, all of which are herein incorporated by reference in their entirety). These methods, however, measure light from the entire seed to calculate average intensities, and therefore are not capable of providing information about single seeds beyond whole seed averages.
Other conventional analytical techniques, such as gas chromatography, also often fail to provide an efficient method for single seed analysis. For example, the conventional method for single seed analysis of canola requires manual excision of one half of each seed for fatty acid analysis by gas chromatography, while the other half is planted. Because of the manual sample preparation and the low throughput of this analytical technique, only a small number of samples can be run per hour using this process.
Although single seed analysis is desirable, conventional spectrometers and sampling methods do not allow for efficient processing of single seeds. Conventional techniques require extensive manual input, which limits the rate of development of plants with improved characteristics.
Conventional spectrometric analysis techniques do not allow for the localization of chemical component levels within different tissues of seeds. Conventional approaches, such as manual dissection of the seed followed by chemical analysis by traditional analytical techniques, are not only laborious and destructive, they also results in poor resolution of the components and poor quantitation, since the sample size resulting from dissection of individual seeds is below the sample size at which most traditional techniques produce reliable results.
Certain conventional imaging systems image the entire sample simultaneously using a tunable filter to limit light from a sample to a single wavelength (see Archibald et al., xe2x80x9cDevelopment of Short-Wavelength Near-Infrared spectral Imaging for Grain Color Classification,xe2x80x9d SPIE Vol. 3,543, 1998, pp. 189-198, which is herein incorporated by reference in its entirety). This method has limited usefulness because even illumination of the sample is difficult to achieve. Uneven illumination of the sample causes areas of low image quality, which limits the accuracy of any information gained from the system. Further, the use of tunable filters is time consuming, which significantly slows the analytical process.
Needed in the art are devices and methods for rapid analysis of bulk and single seeds that can efficiently and non-destructively analyze the morphological or chemical characteristics of individual seeds, and that can be integrated into an agricultural processing machine. The present invention provides such devices and methods.
The present invention provides devices and methods for real time, non-destructive analysis of the physical and chemical characteristics of one or more seeds. Analysis can be carried out by directing light at a sample, which forms transmitted or reflected light. Transmitted or reflected light from the sample can then be dispersed into different wavelengths, which are detected with a datapoint array. Signals produced by the datapoint array can be used to determine the value of any of many chemical and morphological traits.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted light; (C) passing the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a plant tissue exhibits a trait comprising: (A) providing the plant tissue in a sampling device; (B) directing light from a light source to the plant tissue, thereby forming transmitted or reflected light; (C) passing the transmitted or reflected light through a spectrograph, thereby forming dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the plant tissue exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light; (C) dispersing the reflected light to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted light; (C) dispersing the transmitted light to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a plant tissue exhibits a trait comprising: (A) providing the plant tissue in a sampling device; (B) directing light from a light source to the plant tissue, thereby forming transmitted or reflected light; (C) dispersing the transmitted or reflected light to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the device; and, (F) determining whether plant tissue seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a method for determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming transmitted light; (C) passing the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a method for determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming reflected light and transmitted light; (C) passing the reflected light or the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a method for determining whether a seed exhibits multiple traits comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits each of the traits based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits multiple traits comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted light; (C) passing the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits each of the traits based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits multiple traits comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light and transmitted light; (C) passing the reflected light or the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether the seed exhibits each of the traits based on the signals.
The present invention includes and provides a method for selecting a seed having a trait, comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted or reflected light; (C) passing the transmitted or reflected light through a spectrograph; (D) receiving the transmitted light or reflected light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the device; (F) determining whether the seed exhibits the trait based on the signals; and (G) selecting the seed having the trait based on the signals.
The present invention includes and provides a method of introgressing a trait into a plant comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to a seed and generating transmitted or reflected light; (C) passing the transmitted or reflected light through a spectrograph; (D) receiving the transmitted light or reflected light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the device; (F) determining whether the seed exhibits the trait based on the signals; (G) selecting the seed having the trait based on the signals; (H) growing a fertile plant from the seed; and, (I) utilizing the fertile plant as either a female parent or a male parent in a cross with a second plant.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light, wherein a first line of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light, wherein one or more subsequent lines of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted light; (C) passing the reflected light through a spectrograph to form dispersed light, wherein a first line of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming transmitted light; (C) passing the reflected light through a spectrograph to form dispersed light, wherein one or more subsequent lines of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light and transmitted light; (C) passing the reflected light or the transmitted light through a spectrograph to form dispersed light, wherein a first line of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for determining whether a seed exhibits a trait comprising: (A) providing the seed in a sampling device; (B) directing light from a light source to the seed, thereby forming reflected light and transmitted light; (C) passing the reflected light or the transmitted light through a spectrograph to form dispersed light, wherein one or more subsequent lines of the reflected light from the sample passes through the spectrograph; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; (F) repeating steps (A) through (E) for subsequent lines of the reflected light; and, (G) determining whether the seed exhibits the trait based on the signals.
The present invention includes and provides a method for simultaneously determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming reflected light; (C) passing the reflected light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a method for simultaneously determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming transmitted light; (C) passing the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a method for simultaneously determining whether a batch of seeds contains seeds which exhibit a trait comprising: (A) providing the batch of seeds in a sampling device; (B) directing light from a light source to the batch of seed, thereby forming reflected light and transmitted light; (C) passing the reflected light or the transmitted light through a spectrograph to form dispersed light; (D) receiving the dispersed light in a light measuring device comprising an array of multiple datapoints; (E) outputting a signal for each of the multiple datapoints with the light measuring device; and, (F) determining whether members of the batch of seed exhibits the trait based on the signals, wherein the determining comprises associating the members with corresponding datapoints.
The present invention includes and provides a device for measuring properties of agricultural products, comprising: a processing device for producing a sample; a sampling device for providing a sample, wherein the sampling device is disposed to receive the sample from the processing device; and, an optical spectroscopic imaging system, wherein the system is disposed to analyze the sample in the sampling device.
The present invention includes and provides a device for measuring properties of agricultural products, comprising: a sampling device for providing a sample; an optical spectroscopic imaging system, wherein the system is disposed to analyze the sample in the sampling device; and, a sorting device for sorting the sample into two or more different groups, wherein the sorting device is disposed to receive the sample from the sampling device.
The present invention includes and provides a device for measuring properties of agricultural products, comprising: a processing device for producing a sample; a sampling device for providing a sample, wherein the sampling device is disposed to receive the sample from the processing device; an optical spectroscopic imaging system, wherein the system is disposed to analyze the sample in the sampling device; and, a sorting device for sorting the sample into two or more different groups, wherein the sorting device is disposed to receive the sample from the sampling device.